Code division multiple access (CDMA) communication systems are used extensively in satellite communications with military and commercial applications. These systems are also known as CDMA spread spectrum communication systems because the communicated information is spread over a wide allocated frequency spectrum and the frequency spectrum can be re-used multiple times.
Because CDMA modulation techniques are inherently more susceptible to fading conditions generally present at the terrestrial and land mobile environments, their application has been limited to satellite communications. However, with recent advancements in digital signal processing capability, CDMA communication systems are becoming increasingly popular in terrestrial land mobile environments. For example, recent developments have allowed CDMA systems to be used in cellular telephone environments. In general, there are two types of CDMA communication systems. One is known as a frequency hopping CDMA system where the wide allocated spectrum is divided into a substantial number of narrower frequency bands, wherein an information signal is switched or "hopped" over these frequency bands in accordance with a predetermined code. The other CDMA system is known as a direct sequence CDMA communication system (DS-CDMA) where the user information signals, in the form of binary bits, are spread over the allocated frequency spectrum by combining them with spreading codes known as pseudorandom noise (PN) codes. The spreading code comprises a predetermined sequence of binary states known as chips. Conventionally, the CDMA transmitters produce DS-SS communication signals by multiplying user information bit sequences by the spreading chip sequences which are identified with particular receivers. In typical CDMA communication systems, the receivers have prior knowledge of the spreading chip sequences directed at them and decode the DS-SS communication signal based on the known spreading chip sequences.
CDMA receivers, in addition to receiving a desired DS-SS signal, also receive multiple-access DS-SS interfering signals. When there is a large power disparity between the desired signal and the interfering signals, non-zero cross-correlations among the spreading sequences give rise to a phenomenon known as the "near-far" problem. In near-far situations, higher power interfering signals overwhelm the lower power desired signal significantly, thus degrading reception quality at the receiver. One conventional approach to improving the near-far problem uses a power control scheme where the powers from the receivers are fed back to control the interfering transmitter's power as to remove the power disparity. In another solution, PN codes are constructed to be orthogonal to each other. Orthogonal codes produce zero cross-correlation over a predetermined time interval among the desired and interfering chip sequences. As such, interfering signals with orthogonal chip sequences become suppressed during the demodulation process at the receivers.
A more recent approach proposes an adaptive despreading or demodulation process. In an adaptive CDMA system, the receiver is enabled to suppress multiple access interference using adaptive equalization methods. The equalization methods utilize minimum mean square error (MMSE) criterion, whereby a transmitted training bit sequence coded with a spreading chip sequence is equalized with an uncoded reference sequence. In such a system, CDMA transmitters transmit a training bit sequence and the receivers adaptively determine, based on the training sequence, the despreading codes by converging or minimizing the error between the received training bit sequence and the reference bit sequence. Adaptive determination of the despreading chip sequence and suppression of multiple access interference allows a significant number of users to communicate with each other over a spread spectrum channel without requiring prior knowledge of system parameters or power control mechanism.
For adaptive implementation of interference suppression based on the MMSE criterion, either one of the least mean square (LMS) or recursive least mean (RLS) algorithms may be employed. These algorithms utilize mathematical computation and matrix operations to minimize the error between the received training sequence and the reference bit sequence. However, the LMS algorithm is known to have a slow convergent rate when an interfering signal is significantly stronger than the desired signal. On the other hand, the recursive least square (RLS) algorithm has a faster convergent rate than the LMS algorithm, and the convergent rate of the former algorithm does not depend on the ratio of interfering signal to the desired signal. However, the RLS algorithm cannot be used in the DS-CDMA case when the number of transmitters is less than the number of chips and noise power is relatively small with respect to the signal power. These conditions produce a received input correlation matrix with zero or near-zero eigen values. An input correlation matrix is defined as a weighted sum of matrix produced by the product of an input vector by its own transposed vector. These zero or near-zero eigen values cause an eventual divergence in the error minimization process using RLS algorithm.
In mobile communication environments, it is required to quickly track varying channel characteristics and to provide a fast communication links. As explained above, the conventional LMS approaches for converging and minimizing the error between the reference signal and the received signal are time consuming. Therefore, there exists a need for accelerating adaptive equalization process, whereby error minimization could be achieved in a significantly shorter period of time than is achievable by conventional methods which use RLS and LMS algorithms.